Inventory Planning Blog

Effective inventory replenishment planning is a critical process for any company whether manufacturer, distributor or retailer. Planners and purchasing personnel rely heavily on their suppliers to have the items they need as they need them. But, suppliers have the same replenishment challenges and they also rely heavily on their suppliers and or manufacturing units.

How should a planners set the reorder point and reorder quantity (or order-up-to level) for thousands of items, perhaps at multiple locations? Due to the absence of an ‘intelligent’ or advanced planning system, three commonly used approaches have been manual spreadsheet planning, Economic Order Quantity (EOQ), and periods.

Using hard work and hundreds of hours, planners examine each item at each stocking location and manually set the min and max controls. This is such a time-intensive process that the results get out of date, yet nobody has the time to update them. Moreover, without good tools there is no guarantee that the controls will be set well even at the start. Plus, the number of errors is exceptionally high.

Economic Order Quantity (EOQ), a simple calculation of the reorder quantity as a tradeoff between the cost of carrying inventory and the cost of placing an order, is another commonly used approach. Frequent re-orders minimize inventory holding, but incur high ordering costs. Likewise, buying in quantity reduces the ordering cost, but results in low inventory turns and high carrying costs. Although EOQ calculations are frequently available in Enterprise Resource Planning (ERP) systems, planners have difficulty determining the two driving parameters, order cost, and inventory holding cost.

Another common approach is to apply “periods of supply” for the max quantity. For example, average demand may be 120 units per week over the last four months. Taking 2 weeks of stock for the min and 8 weeks for the max, this approach would calculate min of 240 units and max of 960. Such an approach has the advantage of being easy to calculate. Although it is safe for high volume items, it works poorly for low and medium volume items.

The biggest problems with both EOQ and ‘periods of supply’ are neither of them: 1). fully considers the real potential or level of a spike in demand; 2). the impact of short life cycles; or 3). the timing of trend or seasonal changes. These inefficiencies combined with situations where the planner may not have a system that handles ‘every’ item requiring to be planned accounts, for the over or under buying that occurs daily. Trying a moving average whether 3 or 6 months misses the spikes and lows in demand causing stock outs at some times and overstocks at other times.

A better approach is to employ several different methods that more precisely match an item’s expected demand over time. But this is also challenging tracking different replenishment methods for different items or groups of items. There is no substitute, time, money, intelligence or luck, that can match the speed and effectiveness of an advanced inventory planning and optimization solution. These solutions can automatically calculate the optimal replenishment model and quantity easing the burden from the planner.

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